• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.704-709
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• 1993

In this paper, a method of using a look-up table for a fuzzy logic controller is proposed. A look-up table is designed for a fast inference. An algorithm for an inference is developed with a view to decrease execution time. The performance of the developed fuzzy controller is compared with that of the traditional one.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.3
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• pp.101-108
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• 2016

I propose a hybrid fuzzy controller with a look-up table to improve the performance of the FARMA(Fuzzy Auto-regressive Moving Average) fuzzy controller. The hybrid structure of the proposed method is composed of a fuzzy controller with a look-up table of the PD type and the FARMA fuzzy controller. The proposed method improves poor performance due to the lack of I/O data to calculate predictive output and shows robust performance over the FARMA fuzzy controller when a incorrect Dmax value is selected by trial and error. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results with those of the FARMA fuzzy controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.761-765
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• 1997

Our study of rider's postulator stability and tracking control on a unicycle began form the observation of a human riding. The system including unicycle and human operationg his unicycle is a fuzzy intelligent biomechanical model on basis of instinct and intuition search mechanisms. We proposed a robotic unicycle with one wheel and one body as a basic mode and derived equation of motion to this model. Our works is in making out fuzzy look-up table to control robotic unicycle. Fuzzy look-up table were determined for staight line and curve under reasonable inference emulating human's instinct and intuition riding a unicyale. Simulation results show that postulator stability and tracking control on both straight line and curve were successful by using proposed each fuzzy look-up table.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.167-173
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• 2002

The look up table method conventionally applied to control the inner temperature and humidity of a laver drying machine has repeatedly occurred not only laver's damage but also inferior goods since the reaching time at the optimum state takes a long time. In this paper, a fuzzy control theory instead of the look up table was proposed to reduce the reaching time at the optimum state. The proposed method used six input variables and four output variables for the fuzzy control, and a triangle rule for a fuzzifier, The Mandani's min-max method was applied to a fuzzy inference. Also, the mean method of maximum was applied to a defuzzifier. The method applied to the fuzzy controller contributed to reduce the reaching time at the optimum state, and to minimize not only laver's damage but also inferior goods.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.127-130
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• 1995

Fuzzy controllers have proven to be powerful in controlling dynamic processes where mathematical models are unknown or intractable and ill-defined. The way of improving the performance of a fuzzy controller is based on making up rules, constructing membership functions, selecting a defuzzification method and adjusting input-output scaling factors. But there are many difficulties in tuning those to optimize a fuzzy controller. So, in this paper, we propose the look-up table based self-orgenizing fuzzy controller (LSOFC) which optimizes look-up values resulting from the above fuzzy processes. We use the plus-minus tuning method(PMTM), scanning the value through the processes of addition and subtraction. Simulation results demonstrate that the performance of LSOFC is far better than that of a non-tuning fuzzy controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.35-44
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• 1994

In this paper, we propose a new modification method of the look-up table in self-organizing fuzzy control using look-up table. This method has the property that look-up table is modified to have fast response property. Its principle is that the controller forces the trajectory to go into the fast respose region which the error change amount is larger than the error at initial time whenever the reference or disturbance change. Also we introduce the variable learning speed coefficient which is proportional to distance from switching curve. And to demonstrate the applicability of the proposed method, we had simulation study for some examples and esecuted pole balance experiments with inverted pendulum.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.125-130
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• 1995

Recently, the vehicle engine requried precision control of Air-Fuel rate and rigid restriction of exhaust gas. Therefore, we demanded excellent measuring equipment so as to improve of engine performance. Specially, throttle valve control is very important part in the engine control, because structure of engine dynamometer system is very important part in the engine control, because structure of engine dynamometer system is very complicate and it has nonlinear elements which is influenced of disturbance about vibration, a heat, a cooling, energy loss so on. In this study, we propose the method that the control technique using Fuzzy Look-up table and we obtained the satisfying result from realized the control system.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.682-684
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• 1995

The most effective way to improve the performance of a fuzzy controller may be to optimize look-up values. Look-up values are derived from processes used input-output scale factors, membership functions, rule base, fuzzy inference method and defuzzification. It is powerful way to modify or organize look-up table values. In this paper, We propose the look-up values self-organizing fuzzy controller(LSOFC). We use the plus-minus tuning method(PMTM), scanning values through the processes of addition and subtraction. We show the efficiency of this LSOFC by the results of simulation for nonlinear time-varying plant with unmodelled dynamics.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.198-207
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• 1996

Electro sensitive traffic system can't consider passenger car unit, so, it causes start up delay time and passenger waiting time. In this paper, it antecedently creates optimal traffic cycle of passenger car unit at the bottom traffic intersection. But, sometimes it can make mistakes due to changes in car weight, car speed, and control of feed-back data. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.